1. Field of the Invention
The present invention relates to a method and system for beamforming signals. More specifically, the present invention beamforms signals received in sparse, irregular sensor arrays by grouping sensors into clusters, beamforming the signals at each cluster independently of other clusters, and creating a composite response representative of the magnitude and heading of the signals by combining the beamformed responses from each cluster.
2. Description of the Related Art
Beamforming is a method used to process waveform signals such as acoustic, radar or sonar signals detected by an array of sensors. When a source generates a signal that is detected by an array of sensors, beamforming provides a way to determine the magnitude and angle-of-arrival, or azimuth, of the detected signal relative to the array of sensors. For example, the bearing of a ship relative to an array of sensors deployed near the ship may be determined by beamforming the acoustic or sonar signals detected by the array of sensors.
Systems using beamform processing typically include an array of sensors that are linked to signal processing equipment. When an object emits a signal within the detecting range of the beamforming system, the sensors in the array collect and transmit the signal to the processing equipment where the beamforming process is performed. The signals are converted from analog to digital signals by an analog to digital converter either at the sensors or at the processing equipment. During beamforming, the signals detected by each of the sensors are compared to determine the magnitude or power of the detected signal at various azimuths relative to the sensor array. In this manner, the bearing or azimuth of the signal is determined.
There are several beamforming algorithms known to those skilled in the art that may be implemented by beamform systems. Two widely accepted beamforming algorithms are delay and sum beamforming and Fast Fourier Transform (xe2x80x9cFFTxe2x80x9d) beamforming. It is not critical to the present invention what type of beamforming algorithm is implemented.
One limitation of existing beamforming systems is that sparse sensor arrays can lead to inaccurate beamforming results. Logistically, it is desirable to use few sensors and distribute them over a great area because sensors can be expensive and difficult to deploy in remote areas. It is also advantageous, logistically, to spread the sensor elements over a great distance to provide the greatest range of detection. The desire to use fewer sensors over a broader area results in thinly populated, or sparse, sensor arrays.
While there are logistical reasons for using sparse sensor arrays, beamforming systems are usually more accurate if more sensors are used, and if they are positioned to create densely packed sensor arrays. If the sensors are positioned too far apart from one another, grating lobes begin to emerge in the beamformed response. Linear and circular acoustic arrays typically have been designed with sensor spacings on the order of one-half wavelength at the highest frequency of operation to avoid grating lobes. If the highest frequency of operation for a beamforming system is 300 Hz, for example, then the sensors must be placed within about 0.5 meters of each other to avoid grating lobes. In addition, when waveform signals such as acoustic signals carry through a propagation medium, such as air, non-uniformity in the propagation medium limits the distance over which the wavefront remains coherent. If sensors are spread too far apart, the effect of this wavefront incoherence becomes more pronounced and severe de-focusing can occur when traditional coherent processing techniques are applied. Finally, if sensors are positioned too far apart, it becomes more difficult for the system to differentiate between signals radiating simultaneously from two different sources.
Another limitation of existing beamforming systems is that they require powerful central processing nodes capable of receiving and beamforming signals detected by all of the sensors. The processing power necessary to receive and beamform all of the signals increases proportionally with the number of sensors in the sensor array. Processing power constraints, therefore, impose a practical limit on the number of sensors connected to the central processing node, and consequently limit the accuracy of the system.
Yet another limitation of existing beamforming systems is that they require broad communications bandwidth to jointly process the signals detected at the different sensors in the sensor array. At some point during the beamforming process, signals or measurements from each of the different sensors must be transmitted to a central processing node for phase or time-of-arrival comparison, depending on the beamforming method used. Typically this transmission between the sensors and the central processing node is accomplished by radio transmitters. The total radio frequency bandwidth required for this aggregation process increases proportionally with the number of sensors in the system. While bandwidth demands may be reduced through pruning in either time or frequency and through the use of data compression, the total bandwidth required will still increase, at least linearly, with the number of sensors in the sensor array. Bandwidth limitations impose a practical limit on the number of sensors connected to the central processing node, and thus limit the accuracy of the system.
Yet another limitation to existing beamforming systems is the power requirements of operating a dense sensor array. Sensors and processing nodes are often battery powered. Sensors on the perimeter of the array draw a relatively high amount of power from their batteries to transmit their signals to the central processing node, whether by wire or radio transmission. The power requirements of the system place design limitations on the size and density of the sensor array. In addition, the central processing node draws a high amount of power to support the beamform processing of all of the sensors in the array.
Therefore, it would be desirable to provide a beamforming system and method that permits sparse, irregular placement of sensors without sacrificing accuracy or performance. It would also be desirable to provide a system and method for detecting and processing signals in which processing and data aggregation in the beamforming process is organized hierarchically in a spatial sense such that processing demands are distributed and available communications bandwith is increased. Finally, it would be desirable to provide a system and method for beamforming signals that operates more efficiently to consume less power.
The present invention is a system and method for beamforming signals that overcomes the aforementioned problems in existing systems. The system of the present invention can include a plurality of sensors for receiving signals. The sensors can be organized into at least one sensor cluster, each sensor cluster including at least one sensor. The sensors can be acoustic, sonar, radar or multi-signal sensors capable of detecting a variety of signal types. The system can include a signal processing node for each sensor cluster that beamforms signals received by sensors in the sensor clusters, and at least one aggregation node for determining a composite response of the beamformed signals. Sensor links transmit signals received by the sensors from the sensors to the signal processing nodes, and signal processing links transmit beamformed signals from the sensor processing nodes to the aggregation node.
According to one embodiment of the invention, sensors links can be wire connectors. In another embodiment of the invention, each sensor can include radio transceivers, and the signal processing nodes can include multi-channel radio transceivers. Sensor links can use radio frequency transmissions between the sensor radio transceivers and the multi-channel radio transceivers.
According to one embodiment of the invention, signal processing node links are wire connectors. In another embodiment of the invention, each aggregation node can include an aggregation node radio transceiver, and each signal processing node can include a multi-channel radio transceiver. Signal processing node links can use radio frequency transmissions between the multi-channel radio transceiver and the aggregation node radio transceiver.
In yet another embodiment of the invention each sensor includes a global positioning system receiver for determining the positions of the sensors.
The method of the present invention can include the steps of deploying an array of sensors in an area, determining the relative positions of the sensors, organizing the array of sensors into sensor clusters wherein each sensor cluster includes at least one sensor, detecting signals in the in the sensors, creating beamformed responses by beamforming the signals detected by the sensors in each sensor cluster such that the signals detected by the sensors in each sensor cluster are beamformed independently of the signals detected by other sensor clusters, and creating a composite response of all the beamformed responses by combining the beamformed responses together.
In one embodiment of the invention, the step of creating a composite response includes the step of multiplying the beamformed responses together such that the composite response, X(k), is:
X(k)=Xl(k)*X2(k)* . . . *Xn(k) * . . . *XN(k),
where Xn(k) is the beamformed response for the nth sensor cluster, and N is the total number of sensor clusters. The beamformed responses can be pre-edited prior to multiplying them together by, for example, removing those beamformed responses that have the highest and lowest magnitudes.
In another embodiment of the invention, the step of creating a composite response includes the steps of performing a low order statistic on each of the beamformed responses, and using the results obtained from the low order statistic to form the composite response.
The present invention overcomes the limitations of existing beamformer systems and methods. The present invention provides a beamforming system and method for processing signals received by sparse, irregular sensor arrays. By organizing sensors into sensor clusters, and beamforming at each individual sensor cluster, the relative distance between any two sensors that are beamformed together is limited by the size of the sensor clusters. The grating lobe effect that is characteristic of arrays with sensors spaced too far apart is minimized by combining individual beamformed responses from each signal processing node to form a composite response.
The present invention also provides a beamforming system and method in which processing and data aggregation in the beamforming process is organized hierarchically in a spatial sense such that processing demands are distributed and available communications bandwith is increased. Because beamforming is performed at each signal processing node, processing demands are distributed across the entire system. Available communications bandwidth is increased because radio frequencies used by the sensors in one cluster to transmit signals to the signal processing node can be reused in other sensor clusters. Sensors are located relatively close to the signal processing nodes, therefore radio links can be accomplished using relatively low transmission power. Low transmission power allows sensor clusters that are distant from one another to reuse the same frequencies without radio interference.
The present invention also provides a beamforming system and method that operates more efficiently to consume less power. Because the sensors are organized into clusters, they transmit to the signal processing nodes across shorter distances, using less power. In addition, because processing is distributed across all signal processing nodes, it is performed more efficiently and with less power.